{"id":29128163,"url":"https://github.com/willie-conway/global-superstore-data-modeling-analysis","last_synced_at":"2025-07-21T17:33:57.485Z","repository":{"id":301589384,"uuid":"884440463","full_name":"Willie-Conway/Global-Superstore-Data-Modeling-Analysis","owner":"Willie-Conway","description":"A comprehensive data modeling and analysis project for the 🌍Global Super Store, focusing on database design 🗃️, sales data analysis 📊, and interactive visualizations 📍 using MySQL 🖥️ and Tableau 📈.","archived":false,"fork":false,"pushed_at":"2025-06-27T16:23:30.000Z","size":22957,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-27T17:31:44.950Z","etag":null,"topics":["business-analytics","business-intelligence","data-exploration","data-modeling","data-preprocessing","data-restructuring","data-visualization","database-design","er-diagram","geographic-analysis","interactive-dashboard","mysql","profit-analysis","sales-analysis","sales-performance","sales-trends","sql","star-schema","tableau","time-series-analysis"],"latest_commit_sha":null,"homepage":"https://public.tableau.com/app/profile/willie.conway2396/viz/GlobalSuperStore_17308735736410/USASalesandProfits","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Willie-Conway.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2024-11-06T18:53:55.000Z","updated_at":"2025-06-27T16:23:33.000Z","dependencies_parsed_at":"2025-06-27T17:44:16.456Z","dependency_job_id":null,"html_url":"https://github.com/Willie-Conway/Global-Superstore-Data-Modeling-Analysis","commit_stats":null,"previous_names":["willie-conway/global-superstore-data-modeling-analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Willie-Conway/Global-Superstore-Data-Modeling-Analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Willie-Conway%2FGlobal-Superstore-Data-Modeling-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Willie-Conway%2FGlobal-Superstore-Data-Modeling-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Willie-Conway%2FGlobal-Superstore-Data-Modeling-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Willie-Conway%2FGlobal-Superstore-Data-Modeling-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Willie-Conway","download_url":"https://codeload.github.com/Willie-Conway/Global-Superstore-Data-Modeling-Analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Willie-Conway%2FGlobal-Superstore-Data-Modeling-Analysis/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":266342809,"owners_count":23914262,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-07-21T11:47:31.412Z","response_time":64,"last_error":null,"robots_txt_status":null,"robots_txt_updated_at":null,"robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["business-analytics","business-intelligence","data-exploration","data-modeling","data-preprocessing","data-restructuring","data-visualization","database-design","er-diagram","geographic-analysis","interactive-dashboard","mysql","profit-analysis","sales-analysis","sales-performance","sales-trends","sql","star-schema","tableau","time-series-analysis"],"created_at":"2025-06-30T01:37:41.916Z","updated_at":"2025-07-21T17:33:57.477Z","avatar_url":"https://github.com/Willie-Conway.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🌍 Global Super Store: Data Modeling and Analysis Project\n\n## 📊 Overview\nThis project involves the data modeling and analysis of sales data for the Global Super Store, a fictional company operating in the USA. The goal was to design and implement a relational database, and then use Tableau to create interactive visualizations for analyzing sales performance across various regions, products, and time periods.\n\nIn September 2024, I completed the following steps:\n- **Data Restructuring**: Transforming raw business data into a structured database. 🗃️\n- **Database Implementation**: Building the database schema in MySQL. 🖥️\n- **Sales Analysis**: Using Tableau to create visualizations that provide insights into sales performance. 📈\n\n## 🛠️ Project Steps and Breakdown\n\n### Step 1: Create an ER Diagram 📝\nThe first step was to design the **Entity-Relationship (ER) Diagram** for the database. This diagram identifies the key entities and their relationships within the store's operations.\n\n#### Entities:\n- **Orders** 🛍️\n- **Customers** 👥\n- **Time** ⏱️\n- **Location** 🗺️\n- **Sales** 💰\n- **Products** 🏷️\n\n#### Relationships:\n- **Orders** are linked to **Customers** and **Products**.\n- Each **Order** has an associated **Shipment**.\n- **Sales** are linked to **Products** and **Locations**.\n\nI used **MySQL Workbench** to create the ER diagram and normalized the database schema to the **third normal form (3NF)** for efficiency.\n\n#### ER Diagram🔍 :\n\n![ER Diagram](https://github.com/Willie-Conway/Data-Modeling-and-Analysis-Project/blob/b9cb01d08d75e80f0b60579968585e5a7a16fc38/Data%20Modeling%20Project/Data%20Modeling%20Project/Screenshots/ER%20Diagram.png)\n\n\n---\n\n### Step 2: Implement the Data Model 🛠️\nOnce the ER diagram was designed, the next step was to implement the data model in **MySQL Workbench**.\n\n#### Steps:\n1. **Forward Engineer**: Export the schema to MySQL and create the necessary tables. 💾\n2. **SQL Execution**: Execute the SQL script to generate the database on the live server. 📜\n\nThe database schema was successfully created, and data could be imported and analyzed.\n\n#### New Database Schema🔧:\n\n![Data Model](https://github.com/Willie-Conway/Data-Modeling-and-Analysis-Project/blob/e45ff7c59a5656bdafc3684bd06aad7cd495aadd/Data%20Modeling%20Project/Data%20Modeling%20Project/Screenshots/Screenshot%202024-09-22%20225420.png)\n\n---\n\n### Step 3: Create a Star Schema ⭐\nTo facilitate efficient querying and analysis, I implemented a **Star Schema** for the sales data. This schema is designed to support dimensional analysis across key business metrics.\n\n#### Components:\n- **Fact Table**: `Sales` (stores total sales, profit, etc.) 💵\n- **Dimension Tables**:\n  - `Product`: Details about the products. 🏷️\n  - `Location`: Information about geographical regions (City, State, Country). 📍\n  - `Time`: Time-related information (Year, Quarter, Month). 📅\n\nThis schema allowed for efficient aggregation and analysis, particularly focused on sales performance by **Product**, **Location**, and **Time**.\n\n#### Star Schema Diagram Example🌟:\n![Star Schema](https://github.com/Willie-Conway/Global-Superstore-Data-Modeling-Analysis/blob/2b678605cf36461f2b8e92a4d25d9c09748973cf/Data%20Modeling%20Project/Data%20Modeling%20Project/Screenshots/Star%20Schema%20Diagram.png)\n\n---\n\n### Step 4: Create a Map Chart in Tableau 🗺️\nThe first interactive visualization was a **Map Chart** showing the sales performance across different states in the USA.\n\n#### Steps:\n1. Drag the **Country** field to the filter card (select USA). 🇺🇸\n2. Place **State** and **Sales** into the **Detail** and **Color** sections, respectively. 🎨\n\nThis map chart gave a visual representation of sales distribution across states, highlighting regions with higher or lower performance.\n\n#### Map Chart🌍:\n\n![Map chart](https://github.com/Willie-Conway/Data-Modeling-and-Analysis-Project/blob/fb93b9f509e02ae3d1b09d69860fd745197bb707/Data%20Modeling%20Project/Data%20Modeling%20Project/Screenshots/Screenshot%202024-09-22%20223609.png)\n\n\n---\n\n### Step 5: Create a Bubble Chart in Tableau 🟠\nNext, I created a **Bubble Chart** to visualize **profits by state**, with additional details like **quantity sold** and **shipping costs** displayed dynamically.\n\n#### Steps:\n1. Apply the **Country** filter (USA). 🇺🇸\n2. Add **State** to the Color section, **Profit** to the Size section, and other data to the Tooltip for interactivity. 🔍\n\nThis chart helped identify regions with the highest and lowest profit margins and allowed users to explore the data interactively.\n\n#### Bubble Chart🫧:\n\n![Bubble chart](https://github.com/Willie-Conway/Data-Modeling-and-Analysis-Project/blob/c29491f513696034c5e1f84bcf15971fb5506cba/Data%20Modeling%20Project/Data%20Modeling%20Project/Screenshots/Screenshot%202024-09-22%20225037.png)\n\n---\n\n### Step 6: Create a Line Chart for Sales Trends 📉\nTo analyze **sales trends over time**, I created a **Line Chart** that focused on states with sales greater than $40,000.\n\n#### Steps:\n1. Drag **Order Date** into the Columns section and **Sales** into the Rows section. 📅\n2. Apply filters to focus on the USA and select states with sales over $40,000. 💵\n\nThe line chart helped to visualize how sales performed over time, with a clear focus on the highest-performing states.\n\n#### Sales Trend Chart📊:\n\n![Sales Trend chart](https://github.com/Willie-Conway/Data-Modeling-and-Analysis-Project/blob/c29491f513696034c5e1f84bcf15971fb5506cba/Data%20Modeling%20Project/Data%20Modeling%20Project/Screenshots/Screenshot%202024-09-22%20224817.png)\n\n---\n\n### Step 7: Create an Interactive Dashboard 📲\nThe final step was to combine all the visualizations into an **interactive dashboard**. This dashboard allows users to view:\n\n- **Sales in USA** (Map Chart) 🌎\n- **Profits in USA** (Bubble Chart) 💸\n- **Sales Trend in USA** (Line Chart) 📈\n\nInteractivity was enabled by using filters. For example, clicking on a specific state in the map chart dynamically updated both the bubble chart and line chart, allowing for a comprehensive view of sales performance.\n\n#### Interactive Dashboard🖥️:\n\n![Interactive Dashboard](https://github.com/Willie-Conway/Data-Modeling-and-Analysis-Project/blob/c29491f513696034c5e1f84bcf15971fb5506cba/Data%20Modeling%20Project/Data%20Modeling%20Project/Screenshots/Screenshot%202024-09-22%20231109.png)\n\n\n# 📹 Demo Video\n\n\u003cdiv\u003e\n    \u003ca href=\"https://www.loom.com/share/e74c2e9d68dc461a92feec2ad3997318\"\u003e\n      \u003cp\u003eGlobal Super Store - Interactive Dashboard - Watch Video\u003c/p\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://www.loom.com/share/e74c2e9d68dc461a92feec2ad3997318\"\u003e\n      \u003cimg style=\"max-width:300px;\" src=\"https://cdn.loom.com/sessions/thumbnails/e74c2e9d68dc461a92feec2ad3997318-a22232212d972304-full-play.gif\"\u003e\n    \u003c/a\u003e\n  \u003c/div\u003e\n\n\n---\n\n## 🏆 Conclusion and Key Takeaways\nBy completing this project, I achieved the following:\n\n- **Database Restructuring**: Designed and implemented a normalized database schema to support scalable queries and analysis. 🔧\n- **Data Modeling**: Created both an ER diagram and a star schema, forming a strong foundation for business intelligence analysis. 📊\n- **Tableau Visualizations**: Developed interactive visualizations that provided actionable insights into sales performance, profits, and trends. 📈\n- **Interactive Dashboard**: The interactive dashboard facilitated data exploration, allowing business users to focus on specific regions or time periods for decision-making. 🎯\n\nThis project demonstrated my ability to design efficient data models, implement them in MySQL, and use Tableau to build impactful, interactive data visualizations for business analysis.\n\n---\n\n## 🛠️ Tools and Technologies Used\n- **MySQL Workbench**: For designing and implementing the database schema. 💻\n- **Tableau**: For creating interactive visualizations and dashboards. 📊\n- **SQL**: For querying and manipulating the data. 👨🏿‍💻\n  \n## 📜 License\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwillie-conway%2Fglobal-superstore-data-modeling-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwillie-conway%2Fglobal-superstore-data-modeling-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwillie-conway%2Fglobal-superstore-data-modeling-analysis/lists"}